SDP Policy Iteration-Based Energy Management Strategy Using Traffic Information for Commuter Hybrid Electric Vehicles

被引:32
作者
Jiao, Xiaohong [1 ]
Shen, Tielong [2 ]
机构
[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China
[2] Sophia Univ, Dept Engn & Appl Sci, Tokyo 1028554, Japan
关键词
hybrid electric vehicles (HEVs); traffic information; energy management; equivalent fuel consumption; stochastic dynamic programming (SDP); POWER MANAGEMENT; AGENT;
D O I
10.3390/en7074648
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper demonstrates an energy management method using traffic information for commuter hybrid electric vehicles. A control strategy based on stochastic dynamic programming (SDP) is developed, which minimizes on average the equivalent fuel consumption, while satisfying the battery charge-sustaining constraints and the overall vehicle power demand for drivability. First, according to the sample information of the traffic speed profiles, the regular route is divided into several segments and the statistic characteristics in the different segments are constructed from gathered data on the averaged vehicle speeds. And then, the energy management problem is formulated as a stochastic nonlinear and constrained optimal control problem and a modified policy iteration algorithm is utilized to generate a time-invariant state-dependent power split strategy. Finally, simulation results over some driving cycles are presented to demonstrate the effectiveness of the proposed energy management strategy.
引用
收藏
页码:4648 / 4675
页数:28
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